produce a flextable describing a generalized linear model produced by function glm.

# S3 method for glm
as_flextable(x, ...)

Arguments

x

glm model

...

unused argument

Illustrations

See also

Examples

if(require("broom")){ dat <- attitude dat$high.rating <- (dat$rating > 70) probit.model <- glm(high.rating ~ learning + critical + advance, data=dat, family = binomial(link = "probit")) ft <- as_flextable(probit.model) ft }
#> Loading required package: broom
#> a flextable object. #> col_keys: `term`, `estimate`, `std.error`, `statistic`, `p.value`, `signif` #> header has 1 row(s) #> body has 4 row(s) #> original dataset sample: #> term estimate std.error statistic p.value signif #> 1 (Intercept) -7.476392694 3.57018899 -2.09411679 0.036249578 #> 2 learning 0.164374512 0.05337819 3.07943220 0.002073956 #> 3 critical -0.000571721 0.04390146 -0.01302283 0.989609583 #> 4 advance -0.061879215 0.04203589 -1.47205666 0.141005579